Robot welding refers to an automated technology that utilizes industrial robots to perform welding operations. It can improve welding quality, efficiency, and safety, while reducing labor costs and environmental pollution. Robot welding is widely used in industries such as automobiles, ships, aviation, electricity, petroleum, and chemical engineering, and is an important component of modern manufacturing. However, there are also some problems and challenges in robot welding that need to be addressed through continuous research and improvement. This article will introduce common problems and solutions in robot welding from the following aspects:

1. Welding quality issues.

Welding quality is an important indicator for measuring the welding performance of robots, which directly affects the strength, durability, and appearance of products. Welding quality issues mainly include weld defects, weld size deviation, and poor weld shape. There are many reasons for these problems, such as:

-The selection of welding parameters is unreasonable. Welding parameters refer to various factors that affect arc characteristics and molten pool behavior, such as current, voltage, wire feeding speed, protective gas flow rate, etc. If the welding parameters are too large or too small, it can lead to unstable arc, deep or shallow molten pool, excessive or insufficient spatter, and thus affect the quality of the weld seam. Therefore, it is necessary to select appropriate welding parameters based on different welding methods, materials, and workpiece shapes, and conduct experimental verification and optimization.

-The posture control of the welding gun is not accurate. The welding gun posture refers to the position and angle of the welding gun relative to the surface of the workpiece, which determines the relative position and direction of the arc and the workpiece, as well as the shape and flow of the molten pool. If the posture control of the welding gun is not accurate, it can lead to inappropriate arc distance, arc deviation from the center of the weld seam, excessive or small arc oscillation, and thus affect the quality of the weld seam. Therefore, it is necessary to select the appropriate welding gun posture based on different weld seam types and positions, and perform precise control and adjustment.

-The assembly error of the workpiece is too large. Workpiece assembly error refers to the dimensional deviation or shape deformation of a workpiece during the assembly process, which affects the relative position and angle between the workpiece and the robot, as well as the flatness and cleanliness of the workpiece surface. If the assembly error of the workpiece is too large, it can lead to the robot being unable to accurately track and locate the weld seam, or cause interference or inappropriate gaps between the arc and the workpiece, thereby affecting the quality of the weld seam. Therefore, it is necessary to strictly process and inspect the workpiece, and use reasonable assembly fixtures and methods.

There are several ways to solve these problems:

-Adopting an intelligent welding system: An intelligent welding system refers to a system that utilizes technologies such as sensors, computers, and communication to achieve real-time monitoring, analysis, and control of the robot welding process. The intelligent welding system can automatically adjust welding parameters and welding gun posture according to changes in welding environment and working conditions, to ensure the stability and consistency of welding quality. An intelligent welding system can also achieve online detection and diagnosis of weld defects, as well as evaluation and feedback on weld quality, thereby improving welding efficiency and reliability.

-Adopting adaptive welding methods: Adaptive welding methods refer to the method of automatically adjusting the robot's motion trajectory and speed based on the size and direction of workpiece assembly errors, to ensure the alignment and tracking of the arc and weld seam. Adaptive welding methods can obtain information such as the position, shape, and width of the workpiece surface or weld seam through various sensors installed on or near the welding gun, such as optical sensors, electromagnetic sensors, ultrasonic sensors, etc., and compare them with preset target values to calculate the amount of correction that the robot needs to make, and implement the correction through the control system. Adaptive welding methods can effectively eliminate or reduce the impact of workpiece assembly errors on welding quality.

-Adopting optimized welding process: The optimized welding process refers to the process of selecting the optimal welding parameters, weld form, welding sequence, displacement method, and other factors based on different robot types, welding methods, material characteristics, workpiece structures, and other factors, taking into account welding quality, efficiency, cost, and other indicators, in order to achieve the optimal welding effect. The optimized welding process can be determined and verified through theoretical analysis, numerical simulation, experimental verification, and other methods, and adjusted and improved according to the actual situation.

2. Welding efficiency issues.

Welding efficiency is an important indicator to measure the productivity of robot welding, which directly affects the output and cost of products. The main ways to improve robot welding efficiency are as follows:

-Improving robot motion speed: Robot motion speed refers to the motion speed of each joint or coordinate axis of a robot during task execution, which determines the time required for the robot to complete the task. Increasing the motion speed of a robot can shorten the time it takes for the robot to move or change its posture in space, thereby increasing the number of tasks completed by the robot per unit time. Improving the speed of robot movement requires considering the following aspects:

Choose the appropriate exercise mode. Motion mode refers to the motion relationship between various joints or coordinate axes of a robot during task execution, such as linkage mode, independent mode, hybrid mode, etc. Different motion modes can affect the distribution and variation of robot motion speed. Generally speaking, in linkage mode, each joint or coordinate axis starts and ends motion simultaneously, and the motion speed is determined by the slowest joint or coordinate axis. This can ensure the continuity and accuracy of the robot's motion, but also reduce the robot's motion efficiency. In independent mode, each joint or coordinate axis starts and ends motion separately, and the motion speed is determined by its own parameters. This can improve the robot's motion efficiency, but also reduce the robot's motion coherence and accuracy. In mixed mode, each joint or coordinate axis starts and ends its motion in a certain order and rules, and the motion speed is determined by a certain algorithm. This can ensure the continuity and accuracy of the robot's motion while improving its motion efficiency. Therefore, it is necessary to select appropriate motion modes based on different welding tasks and conditions, and make corresponding optimizations and adjustments.

-Adopting an intelligent welding system: An intelligent welding system refers to a system that utilizes technologies such as sensors, computers, and communication to achieve real-time monitoring, analysis, and control of the robot welding process. The intelligent welding system can automatically adjust welding parameters and welding gun posture according to changes in welding environment and working conditions, to ensure the stability and consistency of welding quality. An intelligent welding system can also achieve online detection and diagnosis of weld defects, as well as evaluation and feedback on weld quality, thereby improving welding efficiency and reliability.

-Adopting optimized welding process: The optimized welding process refers to the process of selecting the optimal welding parameters, weld form, welding sequence, displacement method, and other factors based on different robot types, welding methods, material characteristics, workpiece structures, and other factors, taking into account welding quality, efficiency, cost, and other indicators, in order to achieve the optimal welding effect. The optimized welding process can be determined and verified through theoretical analysis, numerical simulation, experimental verification, and other methods, and adjusted and improved according to the actual situation.

In short, robot welding is an efficient, high-quality, and safe welding technology, but there are also some problems and challenges that need to be solved through continuous research and improvement. This article introduces common problems and solutions of robot welding from two aspects: welding quality issues and welding efficiency issues, including the use of intelligent welding systems, adaptive welding methods, and optimized welding processes. These methods have their own advantages and limitations, and need to be selected and combined based on different robot types, welding methods, material characteristics, workpiece structures, and other factors to achieve the best welding effect. There is still much room for improvement and development in robot welding technology. It is hoped that this article can provide some reference and inspiration for the research and application of robot welding technology.